ArticleJournal of educational evaluation for health professions2023
Efficacy and limitations of ChatGPT as a biostatistical problem-solving tool in medical education in Serbia: a descriptive study
Article in Journal of educational evaluation for health professions, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Generative Artificial Intelligence for Data Analysis: A Randomised Controlled Trial in a Public Health Research Institute.International journal of public health · 2025Trial
- Statistical analysis using ChatGPT in medical research.Obstetrics & gynecology science · 2025Article
- Artificial Intelligence: The Prevalent Coauthor Among Early-Career Surgeons.International journal of spine surgery · 2025Article
- Applications, Challenges, and Prospects of Generative Artificial Intelligence Empowering Medical Education: Scoping Review.JMIR medical education · 2025Article
- ChatGPT in Medical Education: Bibliometric and Visual Analysis.JMIR medical education · 2025Review
- ChatGPT as a Tool for Biostatisticians: A Tutorial on Applications, Opportunities, and Limitations.Statistics in medicine · 2025Article
- ChatGPT's performance in sample size estimation: a preliminary study on the capabilities of artificial intelligence.Family practice · 2025Article
- ChatGPT-Assisted Deep Learning Models for Influenza-Like Illness Prediction in Mainland China: Time Series Analysis.Journal of medical Internet research · 2025Article
- Article
- From statistics to deep learning: Using large language models in psychiatric research.International journal of methods in psychiatric research · 2025Review
- ChatGPT for Univariate Statistics: Validation of AI-Assisted Data Analysis in Healthcare Research.Journal of medical Internet research · 2025Article
- ChatGPT and Other Large Language Models in Medical Education - Scoping Literature Review.Medical science educator · 2025Review
- Assessing the Current Limitations of Large Language Models in Advancing Health Care Education.JMIR formative research · 2025Article
- Assessing the accuracy and efficiency of Chat GPT-4 Omni (GPT-4o) in biomedical statistics: Comparative study with traditional tools.Saudi medical journal · 2024Article
- A Comparative Evaluation of Statistical Product and Service Solutions (SPSS) and ChatGPT-4 in Statistical Analyses.Cureus · 2024Article
- In-depth analysis of ChatGPT's performance based on specific signaling words and phrases in the question stem of 2377 USMLE step 1 style questions.Scientific reports · 2024Article
- Article
- Comparing the Performance of ChatGPT-4 and Medical Students on MCQs at Varied Levels of Bloom's Taxonomy.Advances in medical education and practice · 2024Article
- Opportunities, challenges, and future directions of large language models, including ChatGPT in medical education: a systematic scoping reviewJournal of educational evaluation for health professions · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study aimed to assess the performance of ChatGPT (GPT-3.5 and GPT-4) as a study tool in solving biostatistical problems and to identify any potential drawbacks that might arise from using ChatGPT in medical education, particularly in solving practical biostatistical problems.
methodsChatGPT was tested to evaluate its ability to solve biostatistical problems from the Handbook of Medical Statistics by Peacock and Peacock in this descriptive study. Tables from the problems were transformed into textual questions. Ten biostatistical problems were randomly chosen and used as text-based input for conversation with ChatGPT (versions 3.5 and 4).
resultsGPT-3.5 solved 5 practical problems in the first attempt, related to categorical data, cross-sectional study, measuring reliability, probability properties, and the t-test. GPT-3.5 failed to provide correct answers regarding analysis of variance, the chi-square test, and sample size within 3 attempts. GPT-4 also solved a task related to the confidence interval in the first attempt and solved all questions within 3 attempts, with precise guidance and monitoring.
conclusionThe assessment of both versions of ChatGPT performance in 10 biostatistical problems revealed that GPT-3.5 and 4’s performance was below average, with correct response rates of 5 and 6 out of 10 on the first attempt. GPT-4 succeeded in providing all correct answers within 3 attempts. These findings indicate that students must be aware that this tool, even when providing and calculating different statistical analyses, can be wrong, and they should be aware of ChatGPT’s limitations and be careful when incorporating this model into medical education.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.